1,097 machine-learning-"https:"-"https:"-"https:"-"FIIB-HUIS-HUHEN" Fellowship positions
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to protect American agriculture. Learning Objectives: Under the guidance of a mentor, the fellow will learn techniques related to chemistry, molecular biology, and microscopy during the development phase and
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on the effectiveness of mathematics interventions using randomized trials and other methodologies. Areas of focus might include mathematics assessment and discourse, examine the validity of research-based learning
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Vessel Disease group. You will learn and perform physiological assessments including transcranial Doppler and cardiovascular physiology, MRI imaging studies including respiratory gas challenges, as
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 3 days ago
to increase ANDA review efficiency and quality. Use and development of artificial intelligence (AI), machine learning (ML) and large language models (LLMs) to help promote business intelligence in the Agency
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Geosciences division is hiring an Autonomous Material Processing Postdoctoral Fellow to help transform how critical materials are produced. In this role, you'll bring together machine learning, real-time
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the Section for Catalysis and Organic Chemistry at the Department of Chemistry. The group has extensive experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and
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are offered an opportunity for an independent research project using lab data to gain experience conducting ecological data analysis, manuscript writing, and publishing in peer-reviewed journals. Learning
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your machine learning expertise to cutting-edge automated optimisation challenges? We are seeking a Research Fellow in Digital Chemistry and Engineering to combine self-optimising flow reactor technology
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: OUH - Cell and tissue dynamics (Bøe) Project description GENESIS is a newly established Life Science Convergence Environment that brings active matter physics, cell biology, and machine learning
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in knowledge representation, in particular, logics for multi-agent systems. Many of the researchers of the DKM group are also affiliated with the Norwegian Centre for Knowledge-driven Machine Learning